Achieving Traceability Across a Manufacturing Supply Chain Alan Campbell, Architect, Autoliv Michael Malgeri, Principal Technologist, MarkLogic

Transcription

1 Achieving Traceability Across a Manufacturing Supply Chain Alan Campbell, Architect, Autoliv Michael Malgeri, Principal Technologist, MarkLogic COPYRIGHT 13 June 2017MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

2 Agenda Impact of Supply Chain and Manufacturing Failures on Business Traceability Challenges in Manufacturing The MarkLogic Advantage A MarkLogic Traceability Case Study Traceability Demo Q&A SLIDE: 2

3 The Impact of Failure

4 Prison Time! Degraded Brand Lost Revenue Greater Costs Lost Customer Loyalty Increased Liability Lost Efficiencies IMPACT of FAILURES Trust Lost Opportunity Premium Freight Greater Risk Compliance Penalties SLIDE: 4

5 Five Most Costly Recalls - Toyota Recalled 10 M cars Unintended acceleration 37 deaths $3.2B costs SLIDE: 5

6 Five Most Costly Recalls - Pfizer Bextra painkiller Heart and skin side effects $3.3B costs SLIDE: 6

7 Five Most Costly Recalls - Volkswagen 11M cars recalled High NOx* levels scandal $7.9B costs * Nitrous Oxide SLIDE: 7

8 Five Most Costly Recalls - Merck Vioxx painkiller 55,000 deaths Increased heart attack Increased stroke $8.9B costs SLIDE: 8

9 Five Most Costly Recalls - Takata Recalled 300 million inflators 16 deaths Costs of $26B SLIDE: 9

10 Food Recall Peanut Corp. Salmonella outbreak Recalled 2,100 products 9 deaths 714 illnesses in 46 states CEO convicted (28 years) Brother convicted (20 years) SLIDE: 10 QA Manager convicted (5 years) "Our government seems to be sending a clear message that poisoning your customers may well land you in jail,"

11 Traceability Challenges

12 Then Cereal Cheerios - Sneakers - Sneakers

13 Now Cereal (breakfast food) Sneakers (athletic wear) Cereal (breakfast food) - Sneakers (athletic wear) -

14 Traceability Challenges in Manufacturing Product Management Worldwide Ops Product complexity is increasing Materials processed in 10s of facilities in 10s of countries Data Integration Manufacturing 360 data is captured in multiple unique systems Downstream changes feed back into Systems of Record (SoRs) Data Synchronization SLIDE: 14

15 Traceability Challenges in Manufacturing cont d Tiered Storage Some data must be maintained and searchable for decades Semantics Data captured at multiple facilities must be related to final shipped product Data must be archived and searchable in non-proprietary format Search Security models must be in place Security SLIDE: 15

16 The MarkLogic Advantage

17 1 Ingest Data As-Is 2 Access the Data Operationalize MARKLOGIC APPROACH TO DATA INTEGRATION Harmonize & Enrich the Data SLIDE: 17 COPYRIGHT 2016 MARKLOGIC CORPORATION. ALL RIGHTS RESERVED.

18 Why MarkLogic Flexible data ingestion Run and Observe SEMANTICS SCHEMA AGNOSTIC Fast access and complex queries ALERTING / ALERTS ANALYTIC FUNCTIONS CLOUD Enterprise features BI TOOLS INTERFACE NODE API REST API JAVA API AUTOMATED FAILOVER ACID TRANSACTIONS TIERED STORAGE ELASCTICITY SLIDE: 18 SEARCH OPTIC API GEOSPATIAL SEARCH

19 A Traceability Case Study

20 A Traceability Case Study Autoliv Intro Traceability w/o Integration Integrating data across multiple systems in a global manufacturing supply chain Answering important traceability questions Leveraging related information A Demo SLIDE: 20

21 Saving Lives EVERY YEAR AUTOLIV S PRODUCTS SAVE OVER 30,000 LIVES AND PREVENTS TEN TIMES AS MANY SEVERE INJURIES SLIDE: 21

22 Superior Global Presence SLIDE: 22

23 Automotive Safety SLIDE: 23

24 Autoliv Size SLIDE: 24

25 Original Challenges Rapid material flow between plants Cumbersome process to identify impacted materials Comprehensive data summarization slow and cumbersome Summary: Data changes constantly and material flow between facilities could occur in less than a 24 hour period, while the containment effort required over a week. Management directed that a solution be identified which could be effective in hours or minutes rather than days when a containment action was required. SLIDE: 25

26 Traceability w/o Integration Quality Select x from y where p = q IT

27 Critical Issues Autoliv produces materials in ~67 facilities in 28 countries Manufacturing data is captured in over 10 unique systems SOME Data must be maintained and searchable for 20 years or more Data captured at multiple facilities is related to the final product shipped to customer Data must be archived and searchable in a non-proprietary format (json, xml, etc.) Maintaining data in local, proprietary repositories is not sustainable and not minable Security requirements must be enforced Reporting capability must be significantly enhanced SLIDE: 27

28 Traceability With Integration Lot supplier ACME SCHEMA AGNOSTIC DATA INTEGRATION MES Data Warehouse REST API

29 Quality Warehouse Goals Provide Central, long term, neutral format, repository for all manufacturing data Provide ability to ask high value traceability questions of data Provide a data mineable repository for product development Manage data life and eliminate long term storage of manufacturing data in local systems SCHEMA AGNOSTIC BI TOOLS INTERFACE SEARCH TIERED STORAGE SLIDE: 29

30 Benefits With Integration FLEXIBLE DATA MODEL Process Engineering Research & Development MES Data Warehouse Quality Engineering DATA HARMONIZATION

31 Traceability Question 1 A lot of raw material has come under question SEARCH What are the impacted items? Have any items shipped? SCHEMA AGNOSTIC SLIDE: 31

32 ALERTS SEARCH Traceability Question 2 An assembly has failed A subcomponent is suspect How is the lot found from which the suspect subcomponent came? What other assemblies have consumed subcomponents from that lot? How can other suspected assemblies be found for additional inspection and test? SLIDE: 32

33 Traceability Question 3 Equipment has been modified The impacts of those modifications have come under question SEARCH How to identify product produced on equipment, during specific time period? SLIDE: 33 SEMANTICS INFERENCE Additional inspection and testing required Are these products still in the plant or further down the value stream?

34 Phase I Accomplishments Current State of Project and Next Steps ü Challenges of questions 1-3 resolved ü Response time down to minutes ü Versus 5-10 days ü 2 people built PoC in 3 weeks ü Traceability Question 1 ü Traceability Question 2 ü Traceability Question 3 SLIDE: 34

35 Phase II Goals Current State of Project and Next Steps Deeper analytics Integrate more data sets Worldwide rollout SLIDE: 35

36 Demo

37 FAILED INFLATOR

38 Summary Information integration Rapid information access Ability to relate information Ability to ask complex questions Enhance traceability for root cause and impact analysis SLIDE: 38

39 Q&A